基于随机森林的高寒草地地上生物量高光谱估算

草地地上生物量（Aboveground biomass,AGB）是衡量草地生产力的关键因素,准确测定草地AGB具有重要意义。高光谱因具有时效性强、不破坏草地等特点被广泛用于草地生理生态指标的测定。本研究提取和计算了海北试验站高寒草地冠层的原始光谱（Original spectrum,OR）反射率、一阶微分光谱（First derivative spectrum,FD）反射率、光谱位置面积参数（Spectral parameters of spectral position and area,PA）和植被指数（Vegetation indices,VI）4种不同类型的特征变量,使用连续投影算法（Successive projections algorithm,SPA）和递归特征消除算法（Recursive feature elimination,RFE）进行特征选择,采用随机森林算法（Random forest,RF）构建草地AGB估测模型。结果表明：在由4种特征变量分别构建的草地AGB估测模型中,基于VI的RF模型精度最高（测试集R²=0.70,RMSE=557.87 kg·ha^-1）,实测AGB与估测AGB的线性R²达到0.72;不同类型特征变量组合构建的草地AGB估测模型中,PA+VI组合的RF模型精度最高（R²=0.71,RMSE=548.97 kg·ha^-1）,实测AGB和估测AGB的线性R²达到0.73。     

A new galago species for South Africa (Primates: Strepsirhini: Galagidae)

The primate fauna of South Africa has historically been viewed as comprising three diurnal cercopithecoid taxa – chacma baboons (Papio ursinus), vervet (Chlorocebus pygerythrus) and samango monkeys (Cercopithecus albogularis) – and two nocturnal lorisoid species – the thick-tailed greater galago (Otolemur crassicaudatus) and the southern lesser galago (Galago moholi). Here we report the positive identification of a third galago species within South Africa’s borders: the Mozambique dwarf galago or Grant’s galago, Galagoides granti (Thomas and Wroughton, 1907). The taxon was previously held to be restricted to Mozambique, eastern Zimbabwe, Malawi and Tanzania, but we have also observed it in the sand forest of Tembe Elephant Park and the Tshanini Community Reserve, near the Mozambique border. The species was formerly mistaken for Galago moholi, erroneously (we believe) extending the range of the latter species into northern KwaZulu-Natal. In South Africa the two small galagos are unlikely to have overlapping ranges: Galago moholi prefers dry savanna woodlands, whereas Galagoides granti is apparently confined to dry sand forest. However, both species may coexist with the larger and more widespread Otolemur crassicaudatus, an inhabitant of moist savanna, forest edge and thicket. The true South African ranges of both small galago species need to be ascertained.     

Detection of Ecballium elaterium in hedgerow olive orchards using a low-cost uncrewed aerial vehicle and open-source algorithms

BACKGROUND

Ecballium elaterium (common name: squirting cucumber) is an emerging weed problem in hedgerow or superintensive olive groves under no tillage. It colonizes the inter-row area infesting the natural or sown cover crops, and is considered a hard-to-control weed. Research in other woody crops has shown E. elaterium has a patchy distribution, which makes this weed susceptible to design a site-specific control strategy only addressed to E. elaterium patches. Therefore, the aim of this work was to develop a methodology based on the analysis of imagery acquired with an uncrewed aerial vehicle (UAV) to detect and map E. elaterium infestations in hedgerow olive orchards.

RESULTS

The study was conducted in two superintensive olive orchards, and the images were taken using a UAV equipped with an RGB sensor. Flights were conducted on two dates: in May, when there were various weeds infesting the orchard, and in September, when E. elaterium was the only infesting weed. UAV-orthomosaics in the first scenario were classified using random forest models, and the orthomosaics from September with E. elaterium as the only weed, were analyzed using an unsupervised algorithm. In both cases, the overall accuracies were over 0.85, and the producer's accuracies for E. elaterium ranged between 0.74 and 1.00.

CONCLUSION

These results allow the design of a site-specific and efficient herbicide control protocol which would represent a step forward in sustainable weed management. The development of these algorithms in free and open-source software fosters their application in small and medium farms. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

明甪直天王殿松木斗拱振动台试验研究

以甪直保圣寺天王殿斗拱为参考对象,进行无缩尺松木斗拱模型的地震台试验研究。通过对斗拱的加速度与动力放大系数变化趋势、斗拱在振动过程中位移响应变化特征、斗拱变形最大时刻和各构件变形最大时刻的滑移位移和回转位移数值对比分析,得出以下结论：地震加速度用于衡量地震烈度,并不能直接反映斗拱试件的最大变形;振动频率的变化对斗拱回转变形的变化起重要作用,振幅是决定各构件水平滑移的主要因素;各构件变形最大值与斗拱整体变形最大值具有很强相关性,其中栌斗和华拱的回转变形对斗拱的整体变形而言,处于支配地位;斗拱的华拱连下昂部分主要起装饰作用,其榫卯连接节点位置在振动过程中较为薄弱,在对实际文物维护修缮过程中应引起重视并采取相关加固措施。     

松花粉破壁方法的比较研究

以松花粉为主要原料,分别采用纤维素酶法、超声波法、发酵法和旋风破碎法对松花粉进行了破壁研究,并从不同角度对几种方法进行了比较。     

湿地松优良半同胞家系蛋白质及糖类对水分胁迫的生理响应

为研究湿地松优良半同胞家系蛋白质及糖类对水分逆境的生理响应，采用盆栽试验和吸光度测定结合的方法，以湿地松普通种子为对照（CK），测定了七个湿地松半同胞家系在正常水分状态（土壤相对含水量为70%）、弱度水分胁迫（土壤相对含水量为55%~60%）、中度水分胁迫（土壤相对含水量为35%~40%）和强度水分胁迫（土壤相对含水量为20%~25%）条件下的可溶性蛋白质、还原性糖、可溶性糖的含量，研究结果表明：无论是不同水分梯度还是不同家系水平，蛋白质、还原性糖、可溶性糖含量的差异均达极显著性水平。随着水分胁迫程度的加剧，各家系蛋白质含量呈先升后降的趋势，在水分胁迫初期，各家系蛋白质含量增加，水分胁迫中、后期各家系蛋白含量呈直线下降；随着水分胁迫的加剧，各家系还原性糖、可溶性糖含量呈直线上升。家系1027、101、464在水分胁迫条件下具有较高的可溶性糖含量，其抗旱性较其它家系要强，是这三个家系速生、高产的生理原因之一。     

基于随机森林回归算法的小麦叶片SPAD值遥感估算

使用机器学习中的随机森林(RF)回归算法构建小麦叶片SPAD值遥感反演模型。以2010—2013年江苏地区试验点稻茬小麦3个生育期(拔节、孕穗、开花)的叶片为材料,结合我国自主研发的环境减灾卫星HJ-1对研究区域进行同步监测,分析了各生育期叶片SPAD值与8种植被指数间的相关性;以0.01水平下显著相关的植被指数作为输入参数,使用RF回归算法构建了每个生育期的小麦SPAD反演算法模型,即RF-SPAD模型,以支持向量回归(SVR)和反向传播(BP)神经网络算法构建的SVR-SPAD模型和BP-SPAD模型作为比较模型,以R2和均方根误差(RMSE)为指标,分析了每个生育期3个模型的学习能力和回归预测能力,结果表明:RF-SPAD模型在3个生育期都表现出最强的学习能力,R2和RMSE在拔节期分别为0.89和1.54,孕穗期分别为0.85和1.49,开花期分别为0.80和1.71;RF-SPAD模型在3个生育期的回归预测能力都高于BP-SPAD模型,高于或接近于SVR-SPAD模型,R2和RMSE在拔节期分别为0.55和2.11,孕穗期分别为0.72和2.20,开花期分别为0.60和3.16。     

基于森林资源节约的出版规范改进研究

针对当前我国森林资源和文字规范工作的实际情况,在统计分析了森林资源流向、书刊发行现状的基础上,从节约资源的角度出发,应用工业工程的理论思想和方法对文字的规范标准及纸张节约等相关问题进行分析研究,提出了具有较强操作性和实际意义的改进方法。     

Prediction of pine mistletoe infection using remote sensing imaging: A comparison of the artificial neural network model and logistic regression model

In this study, the prediction of pine mistletoe distribution in Scots pine ecosystems was explored using remote sensing variables to compare the multilayer perceptron (MLP) artificial neural network (ANN) and logistic regression (LR) model performances. For this purpose, 109 sample plots were distinguished in pure Scots pine forests (natural) in the Eastern Black Sea Region of Turkey. Distinguishing mistletoe-infected stands (69) and uninfected stands (40) was performed with field observations. The variables acquired from Landsat 8 (Level 1) images were used as independent variables for independent-sample t-test, MLP ANN and LR models. Remote sensing variables indicated that mistletoe-infected stands were in drier areas with a lower vegetation-leaf area index. Based on the performance results of both models, the sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV) and accuracy of the MLP ANN model were superior to those of the LR model. The prediction percentages (SEN, SPE, PPV and NPV) of mistletoe-infected stands were better than the prediction percentages of uninfected stands. The prediction accuracies of LR and MLP ANN models were 74.3% and 89.6%, respectively. However, all remote sensing variables were included in the prediction equation of the MLP ANN model, while the thermal infrared 1 (TIRS1) variable was included in the LR model. In the MLP ANN model, the TIRS1 variable also had the highest normalized importance (100%). The area under the curve (AUC) value for identifying the mistletoe-infected stands of Scots pine forests used by the MLP ANN model (0.892 ± 0.034) was higher than in the LR model (0.838 ± 0.039), explaining the more accurate predictions obtained from the MLP ANN model. The MLP ANN model showed much better performance than the LR model. The results of this study are expected to make important contributions to the identification of potential mistletoe-infected areas.     

Artificial inoculation and susceptibility of Pinus armandii to Dothistroma septosporum

Dothistroma needle blight (DNB) is a serious needle disease of conifers that primarily affects pine species (Pinus spp.). Dothistroma septosporum is one of the DNB pathogens that has a diverse range of host species excluding Pinus armandii. In 15 inoculated P. armandii seedlings, D. septosporum acervuli were observed in 43 infected needles of ten seedlings with a mean disease severity of 1.11% at 25 weeks after inoculations, demonstrating the potential of D. septosporum to cause symptoms on the needles of P. armandii via artificial inoculation. The disease severity of P. armandii was similar to the positive control, Pinus nigra (median 0.75 for P. armandii to 0.70 for P. nigra), thus, P. armandii acts under artificial conditions as a susceptible host species.